Today's wireless wide-area networks (WANs), e.g., as utilized for cellular and wireless internet services, suffer from data capacity shortages due to the proliferation of data-hungry devices such as smart phones, tablets, and notebooks. The number of devices accessing wireless networks, and their demand for ever greater data transfer speeds and broadband network capacities, are growing at exponential rates. These data demands are causing severe congestion in the limited radio frequency (RF) bands allocated for such services. In addition, new fixed wireless networks are coming to market as lower-cost and faster-deploying alternatives to fiber-based residential and enterprise broadband services, further compounding these capacity shortages and further saturating existing wireless RF bands.
While integrated circuit technology continues to advance and computing speeds to grow at exponential rates in accordance with Moore's law, the fundamental radio resource limitation arising from spectrum saturation is impeding further capacity improvements in today's wireless networks. As a result, many companies are focusing attention on the under-utilized millimeter-wave (mm-Wave) bands at radio frequencies of 24 GHz and above (e.g., the 60-GHz band). The large amount of untapped spectrum available in these higher bands appears on the surface as a potential remedy for the capacity crunch, especially as recent advances in silicon technology are making radio transceivers in those bands increasingly cost-effective. However, their poor propagation characteristics and higher attenuation factors above 6 GHz are making it difficult to use these bands for wireless access networks, as they require much higher tower densities per unit area than traditional cellular bands.
In parallel, many modern wireless systems have adopted multi-antenna radio architectures, e.g., antenna arrays, and associated spatial multiplexing methods in an effort to secure the needed capacity increases. Their goal is to exploit the spatial diversity afforded by antenna arrays to achieve a capacity multiplier and/or cell densification through extensive frequency reuse. Such spatial processing systems are referred to variously as adaptive arrays, beamforming, multiple-input-multiple-output (MIMO) spatial multiplexing, and space-time-adaptive processing (STAP), to name a few.
Among currently deployed spatial processing methods, the MIMO multiplexing class is most common. MIMO spatial multiplexing is usually implemented using a time-division duplex (TDD) protocol that transmits multiple, independent data streams on various antenna elements during a node's transmit cycle, while the receiving node uses channel sounding information to invert the propagation channel connecting the two node arrays, thus separating and recovering the transmitted streams at the receiving end. (While frequency-division duplexing (FDD) MIMO protocols are also possible, TDD enables more efficient channel sounding procedures.) A drawback of MIMO spatial multiplexing is that it may be susceptible to interference from uncooperative emitters, in so far as such emitters are not designed to participate in the MIMO channel sounding protocols critical to achieving MIMO frequency reuse through channel inversion. A more fundamental drawback of MIMO spatial multiplexing is that it is heavily dependent on channel propagation characteristics for successful operation. For example, most outdoor channels, where most of the capacity crunch is taking place, fall short of the rich multipath diversity needed to support low-noise channel inversion and deliver the capacity improvements promised by MIMO. Accordingly, MIMO spatial multiplexing has proliferated primarily for indoor local-area network (LAN) applications, especially in Wi-Fi product offerings, where outside (uncooperative) signals are attenuated by walls, and the richer indoor multipath channels often support significant MIMO capacity multipliers, e.g., factors of 2 to 4 and sometimes greater.